LAPSE:2023.22601
Published Article
LAPSE:2023.22601
Market Trading Model of Urban Energy Internet Based on Tripartite Game Theory
Jun Liu, Jinchun Chen, Chao Wang, Zhang Chen, Xinglei Liu
March 24, 2023
As an important driving force to promote the energy revolution, the emergence of the energy internet has provided new ideas for the marketization and flexibility of multi-energy transactions. How to realize multi-energy joint trading is a key issue in the development of the energy market. An urban energy internet market trading model among energy suppliers, energy service providers and the large users in the urban area, based on tripartite game theory, is established in this paper. Considering the cost−income function of each market entity and the basic market trading mechanism, a new game-tree search method is proposed to solve the Nash equilibria for the game model. The Nash equilibria of the tripartite game can be obtained, and the market transaction status corresponding to the Nash equilibria is analyzed from the perspective of the market transactions. The multi-energy joint transaction and market equilibria can be easily implemented for the bids and offers of the multiple energy entities in the urban energy internet market.
Keywords
cost-income model, energy internet, market entities, Nash equilibria, tripartite game
Suggested Citation
Liu J, Chen J, Wang C, Chen Z, Liu X. Market Trading Model of Urban Energy Internet Based on Tripartite Game Theory. (2023). LAPSE:2023.22601
Author Affiliations
Liu J: Shaanxi Key Laboratory of Smart Grid, Xi’an Jiaotong University, Xi’an 710049, China
Chen J: Shaanxi Key Laboratory of Smart Grid, Xi’an Jiaotong University, Xi’an 710049, China
Wang C: Shaanxi Key Laboratory of Smart Grid, Xi’an Jiaotong University, Xi’an 710049, China
Chen Z: Shaanxi Key Laboratory of Smart Grid, Xi’an Jiaotong University, Xi’an 710049, China
Liu X: Shaanxi Key Laboratory of Smart Grid, Xi’an Jiaotong University, Xi’an 710049, China
Journal Name
Energies
Volume
13
Issue
7
Article Number
E1834
Year
2020
Publication Date
2020-04-10
Published Version
ISSN
1996-1073
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PII: en13071834, Publication Type: Journal Article
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LAPSE:2023.22601
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doi:10.3390/en13071834
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